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Job Role:- Principal Engineer AI Job Location:- Bengaluru, India Experience:- 10-15 Years Role Summary:- We are seeking a Principal Engineer AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. This is a hands-on technical leadership role focused on building scalable, secure, and high-performance AI infrastructure that enables the deployment of advanced Generative AI, multimodal AI, and autonomous AI solutions across on-premise and cloud environments. Key Responsibilities:- Design and implement end-to-end architectures for agentic AI systems, Generative AI platforms, RAG pipelines, and AI inference workflows. Build scalable AI platforms supporting distributed training, model deployment, and enterprise integration. Optimise system performance, latency, throughput, GPU utilisation, and infrastructure costs. Lead debugging, production incident resolution, performance tuning, and reliability improvements. Develop reusable AI frameworks, SDKs, APIs, connectors, and CI/CD templates. Implement observability, monitoring, logging, tracing, and operational dashboards. Establish engineering standards, architecture governance, testing frameworks, and controlled release processes. Collaborate with research, product, data, and platform teams to translate AI research into production-ready systems. Mentor engineering teams and drive best practices in software engineering, MLOps, and AI platform development. Required Skills:- Strong expertise in AI system architecture, distributed systems, cloud platforms, and scalable backend engineering. Experience with Generative AI, LLM deployment, RAG systems, agentic AI frameworks, and AI orchestration platforms. Proficiency in Python and modern software engineering practices. Experience with MLOps/LLMOps, containerisation, Kubernetes, CI/CD, monitoring, and infrastructure automation. Knowledge of distributed training, GPU optimisation, vector databases, and real-time inference systems. Strong debugging, performance optimisation, and reliability engineering skills. Excellent technical leadership, collaboration, and mentoring abilities. Qualifications & Experience:- Bachelor s, Master s, or PhD in Computer Science, Artificial Intelligence, Software Engineering, or a related field. 10 15 years of experience in software engineering, AI platforms, machine learning infrastructure, or distributed systems. Proven experience designing and delivering large-scale production systems and AI platforms. Experience leading technical architecture, engineering standards, and cross-functional delivery initiatives. Preferred Attributes:- Hands-on principal-level engineering expertise. Strong understanding of security, governance, observability, and production operations. Experience building reusable engineering platforms and developer tooling. Ability to translate advanced AI research into reliable enterprise-grade products. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.